ABSTRACT
Objective To study the morphology and fractal characterization of UHMWPE wear particles by simulation experiment on knee joint, analyze the classification characteristics of wear particles and discuss the correlation between fractal dimension and wear state. Methods The knee joint simulator was used to realize the knee joint wear motion. The forged CoCrMo alloy and UHMWPE were selected as artificial joint prosthesis materials. The wear particle extraction was based on ISO 17853. The automatic extraction and fractal identification system of wear particles were used to investigate fractal characteristics of wear particles. Three kinds of models were established to classify and recognize wear particles, by using the meshing method, cluster analysis and genetic simulated annealing algorithm, respectively. Results The fractal characteristics of UHMWPE single wear particles was very obvious. The fractal dimension calculated by radar fractal method decreased, during the transition from the larger size of strip debris to the smaller size of roundness debris, and the fractal dimension D of spherical debris was close to zero. The weighted sum of squared error values of fractal dimension for wear particle population classification was the smallest by the model of genetic simulated annealing algorithm, and the clustering feature was very obvious. When the wear cycles were low, the large fractal dimension of strip, needle and fibrous abrasive debris with larger fractal dimension had the largest proportion, and the main abrasion modes were the ploughing and spalling wears. With the extension of wear period, the proportion of wear particles with large fractal dimension decreased, and the proportion of flaky, blocky and near-spherical wear particles with low fractal dimension increased clearly. The wear mechanism changed to the fatigue and adhesive wear, and the wear state transited to the composite wear period. During the stable wear period, the proportion of all kinds of abrasive grains changed little. Due to the increase in the number of small particles, the fractal dimension decreased in stable wear state. Conclusions Based on the improved radar graph method, the fractal dimension of wear particles with different profiles could be obtained by automatic extraction and fractal identification system of wear particles. The research findings can be used in shape extraction, fractal dimension calculation and parameter statistics, as well as providing a new digital analysis tool for identification and diagnosis for wear particles of artificial prosthesis.
ABSTRACT
Objective To develop a musculoskeletal multi-body dynamic model of the patient-specific total knee replacement (TKR), and to simulate knee joint biomechanical characters of the patient during right-turn gait. Methods Based on the musculoskeletal dynamic software AnyBody and the method of force-dependent kinematics as well as the related data from a patient with TKR, the corresponding patient specific lower extremity musculoskeletal multi-body dynamic model was constructed and then used to simulate the right-turn gait of the patient. The knee contact forces, motion, muscle activations and ligament forces were predicted simultaneously by inverse dynamics analysis on such right-turn gait. ResultsThe root mean square error of the predicted average tibiofemoral medial contact force and lateral contact force were 285 N and 164 N, respectively, and the correlation coefficients were 0.95 and 0.61, respectively. The predicted average patellar contact force was 250 N. The predicted contact forces and muscle activations were consistent with those in vivo measurements obtained from the patient. In addition, the model also predicted the average range of tibiofemoral rotations of flexion-extension, internal-external, varus-valgus as 3°-47°, -3.4°-1.5°, 0.2°--1.5°, and the average range of tibiofemoral translations of anterior-posterior, inferior-superior, medial-lateral as 2.6-9 mm, 1.6-3.2 mm, 4.2-5.2 mm, respectively. The predicted average peak value of the medial, lateral collateral ligament force and posterior cruciate ligament force were 190, 108, 108 N, respectively. Conclusions The developed model can predict in vivo knee joint biomechanics, which offers a robust computational platform for future study on the failure mechanisms of knee prosthesis in clinic.
ABSTRACT
BACKGROUND:Knee society score of Peking Union Medical Col ege has been promoted and used in the 306th Hospital of PLA for 2 years and we have accumulated some clinical data. OBJECTIVE:To analyze the stability and feasibility for suitable clinical medical practice of knee society score of Peking Union Medical Col ege. METHODS:Fifty-five patients with osteoarthritis of the knee were included, and the patients were divided into three groups:the preoperative group;3 months postoperative fol ow-up group;6 months postoperative fol ow-up group. The measurement results obtained by the application of the scale were compared to those of the Western Ontario and McMaster Universityies Ostroarthritis Index, visual analog scale, and hospital for special surgery score, and then knee society score goodness-of-fit analysis was performed based on the structural equation model. RESULTS AND CONCLUSION:Knee society score performance assessment of the signs and symptoms of osteoarthritis of the knee patients was positively correlated with the pain severity of visual analog scale score;the overal knee society score of the patients after 6-month fol ow-up was significantly improved compared with that before treatment. The knee society score after 3-and 6-month fol ow-up was significantly higher than that before treatment, and the score was quite with the hospital for special surgery score. The overal assessment of the knee society score after treated for 3 and 6 months was improved for more than grade Ⅰ, the visual analog scale score was decreased for more than 30%. The pain assessment items and physiological functional assessment items of Western Ontario and McMaster Universityies Ostroarthritis Index after 6-month fol ow-up were significantly better than those before treatment (Pgoodness-of-fit analysis showed that the scale had good goodness which had scientific nature and application value.